1. Field of the Invention
The present invention relates to product manufacturing.
2. Description of the Related Art
Many manufactured systems, such as computers, incorporate redundant devices into their designs to ensure that the system continues to function even after a device failure. Before failure of any given device occurs, however, the redundant devices are inactive and therefore tend to increase the overall cost of the product along with increasing reliability. Further, different devices have different failure rates, which should be taken into account when selecting which devices to duplicate for redundancy purposes. More particularly, devices having higher failure probabilities are usually made redundant as a matter of course, while devices having lower failure probabilities may or may not be made redundant, depending on the desired system design.
Because greater redundancy leads to higher system costs, a system designer normally tries to balance reliability with costs. Other manufacturing parameters, such as complexity, may also influence the number of redundant units. Systems to be used in applications where reliable operation is critical may consider cost reduction a lower priority and incorporate more redundant units, even for units having lower failure probabilities. The result is a system that may have a higher cost along with its higher reliability. Conversely, systems where low cost is a higher priority than maximum reliability may have fewer redundant devices, which may also reduce the product's reliability.
Further, for devices that are too expensive to make redundant, it is possible to provide redundancy by combining other types of devices that together carry out the same function as the original, more expensive device to improve reliability and keep the system under control. It is also desirable to integrate multiple functionalities into, for example, a single board in the system. Greater integration may increase the cost overhead for the system, but the overall board cost may be less than the sum of the costs of the individual devices. Integration may also necessitate replacement of an entire board if one functionality fails, but the failure probability of the individual devices on the board should be considered to determine the likelihood of this occurrence. Failure probability is normally a factor that determines the composition of the board itself (e.g., which components will be integrated together on a single board).
Capacity is yet another factor to be considered in a system design. The device configuration should adequately meet expected target capacity demands. This places limits on the number and/or configuration of the units incorporated into the system. Thus, given these and other dimensions, maximizing reliability given cost and/or capacity constraints is a complicated task. Other dimensions, such as integration, redundancy of a more expensive device using a combination of less expensive devices, different priorities for reliability and cost, system capacity, etc. make determining an optimum configuration even more complex because there are so many possible combinations and factors to weigh against each other. Determining an optimum configuration and redundancy allocation for a given system design can take many months through trial and error. Further, because trial and error processes necessarily introduce human error, it is difficult to ensure that the configuration obtained by such processes is truly optimized or even quasi-optimized.
There is a desire for a faster, more reliable way to determine an optimal configuration in a system design.